Reliable In-Memory Data Management on Unreliable Hardware

Dirk Habich, Till Kolditz, Juliana Hildebrandt, Wolfgang Lehner

2018

Abstract

The key objective of database systems is to reliably manage data, whereby high query throughput and low query latency are core requirements. To satisfy these requirements, database systems constantly adapt to novel hardware features. Although it has been intensively studied and commonly accepted that hardware error rates in terms of bit flips increase dramatically with the decrease of the underlying chip structures, most database system research activities neglected this fact, leaving error (bit flip) detection as well as correction to the underlying hardware. Especially for memory, silent data corruption (SDC) as a result of transient bit flips leading to faulty data is mainly detected and corrected at the DRAM and memory-controller layer. However, since future hardware becomes less reliable and error detection as well as correction by hardware becomes more expensive, this free ride will come to an end in the near future. To further provide a reliable data management, an emerging research direction will be employing specific and tailored protection techniques at the database system level. Following that, we are currently developing and implementing an adopted system design for state-of-the-art in-memory column stores. In this position paper, we summarize our vision, the current state and outline future work of our research.

Paper Citation

in Harvard Style

Kolditz T. and Lehner W. (2018). Reliable In-Memory Data Management on Unreliable Hardware.In Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA, ISBN 978-989-758-318-6, pages 365-372. DOI: 10.5220/0006884203650372

in Bibtex Style

@conference{data18,
author={Till Kolditz and Wolfgang Lehner},
title={Reliable In-Memory Data Management on Unreliable Hardware},
booktitle={Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,},
year={2018},
pages={365-372},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006884203650372},
isbn={978-989-758-318-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 7th International Conference on Data Science, Technology and Applications - Volume 1: DATA,
TI - Reliable In-Memory Data Management on Unreliable Hardware
SN - 978-989-758-318-6
AU - Kolditz T.
AU - Lehner W.
PY - 2018
SP - 365
EP - 372
DO - 10.5220/0006884203650372